Acute myocardial infarction (AMI) affects approximately 935,000 Americans annually and has a case-fatality rate of 15%.1 significant differences in survival after AMI have been identified by sociodemographic characteristics such as gender and race. Most studies evaluating outcomes after AMI have focused on short-term mortality using traditional estimates such as 30-day and 1-year mortality. These measures can be difficult to apply to individual patients with particular risk profiles, and they fail to accoun for differences in population-based life expectancy by gender and race. Moreover, most studies have been limited to short-term outcomes due to difficulties with patient follow-up. To account for these limitations, we propose the use of two new metrics, life expectancy and years-of-potential-life-lost (YPLLs), to characterize long-term mortality after AMI. These metrics allow for the calculation of age, gender, and race-specific estimates of survival, which can be used to inform decision-making about long-term patient care. In addition, YPLLs account for sociodemographic differences in population-based life expectancy, thereby allowing for more appropriate comparisons of survival between genders and races. The objective of this proposal is to introduce a novel approach for evaluating long-term survival after AMI and to use this approach to evaluate gender and racial disparities. Our central hypothesis is that gender and racial disparities in long-term survival after AMI will become more pronounced after adjustment for population-based life expectancy. SPECIFIC AIMS: This research proposal has three aims. In the first aim, we will calculate gender, age, and race-specific life expectancy estimates for post-AMI patients. We will accomplish this aim by linking data from the Cooperative Cardiovascular Project (CCP), a quality improvement study of Medicare patients with AMI, to mortality data from the Medicare denominator files in order to calculate 15-year outcomes for patients. Parametric survival models will be used to calculate life expectancy. [The second aim will evaluate gender differences in long-term mortality after AMI by comparing unadjusted and adjusted life expectancy estimates by gender and then calculating YPLLs for men and women by comparing life expectancy estimates in the CCP cohort to those in the general Medicare population. The third aim will use a similar approach to that of Aim 2 but will evaluate racial disparities in life expectancy and YPLLs after AMI. If time permits, we will also examine geographic variations in racial disparities after AMI. Specifically, we will compare differences in life expectancy for black and white patients across four U.S. regions.] Public health importance: Characterizing long-term mortality risk has clinical utility for patient management both during the immediate hospitalization and after discharge. Knowing how patient and clinical factors contribute to long-term outcomes allows physicians to identify risk factors that require more careful follow-up, quantify the relative contribution of these factors when weighing management options, and to characterize socio-demographic disparities in long-term mortality.